The properties and characteristics of a polycrystalline material are partially determined by the size and shape of the constituent crystals or grains, the orientation of the crystal lattices, and the spatial location of the crystals. Accordingly, these attributes of the material microstructure must be determined in order to understand why certain materials behave as they do, to predict how other materials will behave, and to alter or otherwise control material forming and processing techniques to improve specific material properties.
Crystal lattice planes are typically identified by a procedure known as crystal indexing. Automated crystal indexing procedures have enabled researchers, material processors, and manufacturers to obtain valuable microstructure information over a relatively large material specimen area. Generally, such a procedure repetitively bombards selected points of a material specimen with a beam of electrons. The electrons interact with a small volume of the material sample at the selected points, and diffracting crystals cause electron backscatter diffraction patterns (EBSPs) to form on a phosphor screen near the specimen. The EBSPs may be imaged through a video camera and digitized for further processing.
Good quality EBSPs include a number of intersecting, relatively high intensity bands that are usually referred to as Kikuchi bands. The Kikuchi bands result from electrons being diffracted from various planes in the crystal lattice at the point of bombardment. An abundance of microstructure information, including the crystal indexing solution, may be obtained by analyzing the various parameters of the Kikuchi bands. Computer-implemented image processing techniques have been developed to analyze Kikuchi bands from EBSPs taken at numerous points on a material sample and to generate displays of the specimen that convey a wealth of microstructure information.
A conventional processing technique utilizes a computational iteration scheme to determine the resultant crystal indexing solution. The indexing solution is calculated a number of times using different computational parameters, and a voting algorithm selects the "best" solution. Unfortunately, this algorithm does little more than rank the different solutions, and no probabilistic measurements or statistical confidence data is included in the analysis. Thus, one must rely on the selected indexing solution without knowing how reliable the data may actually be. Unfortunately, any further analyses or calculations based on an unreliable indexing solution will also be unreliable, and a reviewer may not know that the results are unreliable.
Although there are only seven basic crystal types, there are approximately 40,000 different crystal phase variations. If known, the crystal phase of a material provides structural parameters and geometrical relationships necessary for the determination of other material properties. Thus, the crystal phase is an important characteristic of a material that can be valuable to researchers and scientists. For example, a crystal phase identity is typically assumed when performing crystal indexing processes. Given the identity of the crystal phase, mathematical relationships required to calculate the crystal indices are selected. However, many polycrystalline materials have more than one distinct crystal phase. In addition, other materials may have an unknown phase or an unknown combination of phases. Thus, an indexing solution for such a material may be incomplete or erroneous without a proper identification of the crystal phase or phases within the particular specimen.